Advanced Search
MyIDEAS: Login

Correlated binomial regression models

Contents:

Author Info

  • Pires, Rubiane M.
  • Diniz, Carlos A.R.
Registered author(s):

    Abstract

    In this paper, a class of correlated binomial regression models is proposed. The model is based on the generalized binomial distribution proposed by Luceño (1995) and Luceño and Ceballos (1995). The regression structure is modeled by using four different link functions and the dependence between the Bernoulli trials is modeled by using three different correlation functions. A data augmentation scheme is used in order to overcome the complexity of the mixture likelihood. A Bayesian method for inference is developed for the proposed model which relies on both the data augmentation scheme and the MCMC algorithms to obtain the posterior estimate for the parameters. Two types of Bayesian residuals and a local influence measure from a Bayesian perspective are proposed to check the underlying model assumptions, as well as to identify the presence of outliers and/or influential observations. Simulation studies are presented in order to illustrate the performance of the developed methodology. A real data set is analyzed by using the proposed models.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.sciencedirect.com/science/article/pii/S0167947312000709
    Download Restriction: Full text for ScienceDirect subscribers only.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 56 (2012)
    Issue (Month): 8 ()
    Pages: 2513-2525

    as in new window
    Handle: RePEc:eee:csdana:v:56:y:2012:i:8:p:2513-2525

    Contact details of provider:
    Web page: http://www.elsevier.com/locate/csda

    Related research

    Keywords: Binomial regression models; Generalized binomial distribution; Data augmentation scheme; Bayesian inference; Bayesian residuals; Local influence;

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:56:y:2012:i:8:p:2513-2525. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.